Guided project of analysing data on Star Wars movies


In [1]:
import pandas as pd
star_wars = pd.read_csv("star_wars.csv", encoding="ISO-8859-1")

In [3]:
star_wars = star_wars[pd.notnull(star_wars["RespondentID"])]
star_wars.head(10)


Out[3]:
RespondentID Have you seen any of the 6 films in the Star Wars franchise? Do you consider yourself to be a fan of the Star Wars film franchise? Which of the following Star Wars films have you seen? Please select all that apply. Unnamed: 4 Unnamed: 5 Unnamed: 6 Unnamed: 7 Unnamed: 8 Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. ... Unnamed: 28 Which character shot first? Are you familiar with the Expanded Universe? Do you consider yourself to be a fan of the Expanded Universe?ξ Do you consider yourself to be a fan of the Star Trek franchise? Gender Age Household Income Education Location (Census Region)
1 3.292880e+09 Yes Yes Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 3 ... Very favorably I don't understand this question Yes No No Male 18-29 NaN High school degree South Atlantic
2 3.292880e+09 No NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN Yes Male 18-29 $0 - $24,999 Bachelor degree West South Central
3 3.292765e+09 Yes No Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith NaN NaN NaN 1 ... Unfamiliar (N/A) I don't understand this question No NaN No Male 18-29 $0 - $24,999 High school degree West North Central
4 3.292763e+09 Yes Yes Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 5 ... Very favorably I don't understand this question No NaN Yes Male 18-29 $100,000 - $149,999 Some college or Associate degree West North Central
5 3.292731e+09 Yes Yes Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 5 ... Somewhat favorably Greedo Yes No No Male 18-29 $100,000 - $149,999 Some college or Associate degree West North Central
6 3.292719e+09 Yes Yes Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 1 ... Very favorably Han Yes No Yes Male 18-29 $25,000 - $49,999 Bachelor degree Middle Atlantic
7 3.292685e+09 Yes Yes Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 6 ... Very favorably Han Yes No No Male 18-29 NaN High school degree East North Central
8 3.292664e+09 Yes Yes Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 4 ... Very favorably Han No NaN Yes Male 18-29 NaN High school degree South Atlantic
9 3.292654e+09 Yes Yes Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 5 ... Somewhat favorably Han No NaN No Male 18-29 $0 - $24,999 Some college or Associate degree South Atlantic
10 3.292640e+09 Yes No NaN Star Wars: Episode II Attack of the Clones NaN NaN NaN NaN 1 ... Very favorably I don't understand this question No NaN No Male 18-29 $25,000 - $49,999 Some college or Associate degree Pacific

10 rows × 38 columns


In [4]:
star_wars.columns


Out[4]:
Index(['RespondentID',
       'Have you seen any of the 6 films in the Star Wars franchise?',
       'Do you consider yourself to be a fan of the Star Wars film franchise?',
       'Which of the following Star Wars films have you seen? Please select all that apply.',
       'Unnamed: 4', 'Unnamed: 5', 'Unnamed: 6', 'Unnamed: 7', 'Unnamed: 8',
       'Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.',
       'Unnamed: 10', 'Unnamed: 11', 'Unnamed: 12', 'Unnamed: 13',
       'Unnamed: 14',
       'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.',
       'Unnamed: 16', 'Unnamed: 17', 'Unnamed: 18', 'Unnamed: 19',
       'Unnamed: 20', 'Unnamed: 21', 'Unnamed: 22', 'Unnamed: 23',
       'Unnamed: 24', 'Unnamed: 25', 'Unnamed: 26', 'Unnamed: 27',
       'Unnamed: 28', 'Which character shot first?',
       'Are you familiar with the Expanded Universe?',
       'Do you consider yourself to be a fan of the Expanded Universe?ξ',
       'Do you consider yourself to be a fan of the Star Trek franchise?',
       'Gender', 'Age', 'Household Income', 'Education',
       'Location (Census Region)'],
      dtype='object')

In [5]:
yes_no = {"Yes": True, "No": False}

for col in [
    "Have you seen any of the 6 films in the Star Wars franchise?",
    "Do you consider yourself to be a fan of the Star Wars film franchise?"
    ]:
    star_wars[col] = star_wars[col].map(yes_no)

star_wars.head(3)


Out[5]:
RespondentID Have you seen any of the 6 films in the Star Wars franchise? Do you consider yourself to be a fan of the Star Wars film franchise? Which of the following Star Wars films have you seen? Please select all that apply. Unnamed: 4 Unnamed: 5 Unnamed: 6 Unnamed: 7 Unnamed: 8 Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. ... Unnamed: 28 Which character shot first? Are you familiar with the Expanded Universe? Do you consider yourself to be a fan of the Expanded Universe?ξ Do you consider yourself to be a fan of the Star Trek franchise? Gender Age Household Income Education Location (Census Region)
1 3.292880e+09 True True Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith Star Wars: Episode IV A New Hope Star Wars: Episode V The Empire Strikes Back Star Wars: Episode VI Return of the Jedi 3 ... Very favorably I don't understand this question Yes No No Male 18-29 NaN High school degree South Atlantic
2 3.292880e+09 False NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN Yes Male 18-29 $0 - $24,999 Bachelor degree West South Central
3 3.292765e+09 True False Star Wars: Episode I The Phantom Menace Star Wars: Episode II Attack of the Clones Star Wars: Episode III Revenge of the Sith NaN NaN NaN 1 ... Unfamiliar (N/A) I don't understand this question No NaN No Male 18-29 $0 - $24,999 High school degree West North Central

3 rows × 38 columns


In [6]:
import numpy as np

movie_mapping = {
    "Star Wars: Episode I  The Phantom Menace": True,
    np.nan: False,
    "Star Wars: Episode II  Attack of the Clones": True,
    "Star Wars: Episode III  Revenge of the Sith": True,
    "Star Wars: Episode IV  A New Hope": True,
    "Star Wars: Episode V The Empire Strikes Back": True,
    "Star Wars: Episode VI Return of the Jedi": True
}

for col in star_wars.columns[3:9]:
    star_wars[col] = star_wars[col].map(movie_mapping)

In [7]:
star_wars = star_wars.rename(columns={
        "Which of the following Star Wars films have you seen? Please select all that apply.": "seen_1",
        "Unnamed: 4": "seen_2",
        "Unnamed: 5": "seen_3",
        "Unnamed: 6": "seen_4",
        "Unnamed: 7": "seen_5",
        "Unnamed: 8": "seen_6"
        })

star_wars.head(3)


Out[7]:
RespondentID Have you seen any of the 6 films in the Star Wars franchise? Do you consider yourself to be a fan of the Star Wars film franchise? seen_1 seen_2 seen_3 seen_4 seen_5 seen_6 Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. ... Unnamed: 28 Which character shot first? Are you familiar with the Expanded Universe? Do you consider yourself to be a fan of the Expanded Universe?ξ Do you consider yourself to be a fan of the Star Trek franchise? Gender Age Household Income Education Location (Census Region)
1 3.292880e+09 True True True True True True True True 3 ... Very favorably I don't understand this question Yes No No Male 18-29 NaN High school degree South Atlantic
2 3.292880e+09 False NaN False False False False False False NaN ... NaN NaN NaN NaN Yes Male 18-29 $0 - $24,999 Bachelor degree West South Central
3 3.292765e+09 True False True True True False False False 1 ... Unfamiliar (N/A) I don't understand this question No NaN No Male 18-29 $0 - $24,999 High school degree West North Central

3 rows × 38 columns


In [8]:
star_wars = star_wars.rename(columns={
        "Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.": "ranking_1",
        "Unnamed: 10": "ranking_2",
        "Unnamed: 11": "ranking_3",
        "Unnamed: 12": "ranking_4",
        "Unnamed: 13": "ranking_5",
        "Unnamed: 14": "ranking_6"
        })

star_wars.head(3)


Out[8]:
RespondentID Have you seen any of the 6 films in the Star Wars franchise? Do you consider yourself to be a fan of the Star Wars film franchise? seen_1 seen_2 seen_3 seen_4 seen_5 seen_6 ranking_1 ... Unnamed: 28 Which character shot first? Are you familiar with the Expanded Universe? Do you consider yourself to be a fan of the Expanded Universe?ξ Do you consider yourself to be a fan of the Star Trek franchise? Gender Age Household Income Education Location (Census Region)
1 3.292880e+09 True True True True True True True True 3 ... Very favorably I don't understand this question Yes No No Male 18-29 NaN High school degree South Atlantic
2 3.292880e+09 False NaN False False False False False False NaN ... NaN NaN NaN NaN Yes Male 18-29 $0 - $24,999 Bachelor degree West South Central
3 3.292765e+09 True False True True True False False False 1 ... Unfamiliar (N/A) I don't understand this question No NaN No Male 18-29 $0 - $24,999 High school degree West North Central

3 rows × 38 columns


In [9]:
star_wars[star_wars.columns[9:15]] = star_wars[star_wars.columns[9:15]].astype(float)

In [10]:
star_wars[star_wars.columns[9:15]].mean()


Out[10]:
ranking_1    3.732934
ranking_2    4.087321
ranking_3    4.341317
ranking_4    3.272727
ranking_5    2.513158
ranking_6    3.047847
dtype: float64

In [11]:
%matplotlib inline
import matplotlib.pyplot as plt

plt.bar(range(6), star_wars[star_wars.columns[9:15]].mean())


Out[11]:
<Container object of 6 artists>

In [12]:
star_wars[star_wars.columns[3:9]].sum()


Out[12]:
seen_1    673
seen_2    571
seen_3    550
seen_4    607
seen_5    758
seen_6    738
dtype: int64

In [13]:
plt.bar(range(6), star_wars[star_wars.columns[3:9]].sum())


Out[13]:
<Container object of 6 artists>

In [ ]: